We love new technology at Point of Reference. And being in the Salesforce.com partner ecosystem means we have a steady stream of new “toys” to leverage for clients. So, when Salesforce announced ChatGPT for Slack we were ecstatic. Generative AI has been on our radar since the middle of 2022. By the time this announcement came out we had been contemplating a wide variety of applications for AI in our customer marketing domain. Imagine, you just received a request to use a customer not yet in your program for an advocate activity. ChatGPT for Slack would allow you to ask if that company has any open support cases, what their spend history has been over the last three years, and when their contract renews…and get a cogent, concise answer based on your company’s Salesforce data! How about a quick ChatGPT question concerning when an advocate was last used and for what type of activity? Needless to say, ChatGPT is only as good as the data, but provided it’s reliable, this will be a leap forward to retrieving data.
One thing that exercise made clear was that we have never considered a customer marketing world where relationships weren’t at the center. Every feature we design considers deeply how the humans involved (customer, customer marketer, customer success manager, account executive, etc.) factor in. There’s always an analog equivalent to the digital manifestation.
What we do in customer marketing, though in a business context, is so personal. We ask customers to allocate time, stake their reputation and invest emotionally in us. In the early iteration of Point of Reference, we interviewed our client’s advocates about their customer experiences to create advocate content for sellers’ use. What came through loud and clear in the pre-interview banter was that the customer agreed to be interviewed because of their sales rep, account manager or consultant. It was, without exception, always about the relationship. The customer felt well-cared for and wanted to express their gratitude.
Customer marketers, particularly those who manage customer communities, put a lot of energy into inventing ways to make advocates feel special. We see this within our customer base, and read about it from some of the content creators in our space like Mary Green, Leslie Barrett, Alison Bukowski, Valeria Gomez and agencies like Captivate Collective. This is how we show our gratitude to advocates who invest in a relationship with us. I relate to this type of customer marketer – they get the power of relationships. And that goes for how they think about relationships with internal stakeholders as well.
If the designated customer marketer doesn’t thrive on cultivating and sustaining relationships, then perhaps there’s a better fit elsewhere in the marketing organization (analysis, operations, demand gen, digital). If that marketer’s end goal is to have as little contact as possible with advocates and internal stakeholders by automating every touchpoint, every ask, every reward, then you have a transactional, superficial customer marketing operation, not to be confused with a program. And you’re leaving a lot of goodwill and value to the organization on the table.
There are plenty of places where a relationship can be replaced with automation. Think: ATMs, restaurant reservations, and parking kiosks. But, I place a high value on relationships when it comes to healthcare, insurance and legal related stuff. They’re personal in nature, and not the parts of life where you want to feel like a number or a QR code.
Algorithms and various forms of automation can generate system generated notifications, but they certainly don’t make us feel special. In fact, they mess up just enough (wrong information, bad assumptions, wrong timing) that I’m often quick to ignore or discard them, with a little disgust thrown in.
Customer marketing done well is relationship-intensive. That’s different than labor-intensive, which can be largely solved by practical, intelligent automation. The question in relationship-intensive fields is How do we deepen, expand and elevate relationships? Not, How do we avoid people and still get what we want? The latter may be tempting to an efficiency zealot more comfortable with technology than people. They lose sight of the humanity part of what we do.
Take a common “ask” a customer marketer makes of an advocate. We believe this simple act is full of nuance and that human intelligence plays an important role. First, should the ask even be made? Is the advocate on leave of absence? Are they knee-deep in an internal project? Are they the right advocate? Do they have the necessary perspective, history and expertise for the need? Who is asking? The one making the ask will have a lot to do with the answer.
How would you feel if that ask came quite obviously from a system rather than a person? What if AI could pretty well fake a human ask, but then flubs the interaction a few steps later, exposing the ruse? What was a personal interaction just became a social faux pas—with one of your best customers! The motivation to help is lost because the relationship has been devalued. Didn’t take much to wipe out any accrued goodwill.
That’s not an attractive vision to us. It’s not what’s so alluring and gratifying about customer marketing, where true magic happens in business relationships. So, consider the role of relationships in customer marketing as all forms of new and titillating AI applications flood our world. Assist us? Yes. Substitute for humanity? That’s a hard no. We are in a business that’s powered by relationships, first and foremost. It will be a long time before AI gets the emotional quotient (EQ) part right, if ever.
As we incorporate generative AI and predictive analytics into our customer marketing solution, we won’t allow the glitter of these technologies to ever blind us to what’s at the core of our mission: relationships.
It's only natural that many advocacy leaders have landed on the same objective: make the program easier to use by meeting users where they're already working.
Today, that increasingly means Microsoft Copilot, ChatGPT, Claude, Gemini or whatever generative AI assistant employees happen to have open.
Imagine a salesperson simply asking AI, "Find me three German healthcare customers using product Y, willing to speak with a prospect," instead of navigating to another interface, or waiting for someone from advocacy, or elsewhere, to respond. It's easy to see the appeal. Removing friction has always been one of the fastest ways to increase adoption.
It is exactly the right instinct.
The difficult parts, arguably the reason program managers exist, occur before and after AI says, "Here are your three best matches."
The value advocacy professionals bring is the ability to operationalize and scale customer advocacy for maximum impact. Quality advocate information doesn't just appear, it's the result of a system.
Now that the user has three advocates, what should happen?
Notice what happened. The search was completed.
The next steps are just as manual as ever if AI search is the be all, end all.
Reality Check
AI can tell you who could participate. It can't tell you who should participate unless someone (or something) has been keeping score.
This is where the story starts to feel strangely familiar.
Many companies still operate their program using spreadsheets, scattered CRM fields, shared drives, email folders, and the remarkable memories of a handful of program managers.
Eventually, organizations realize they aren't managing an advocacy program at all. They're managing lists that happen to contain advocates.
But the shortcomings are real:
Purpose-built advocacy platforms emerged because advocacy is much more than a search problem.
Ironically, AI has convinced some organizations to revisit the same shortcut they worked so hard to escape.
Let's imagine two different worlds.
In the first, AI recommends an advocate for a sales call.
Months later, AI knows this customer recently participated and may deserve a break before being asked again.
Now imagine the second world.
Three months later someone asks how many customer reference contributed to the revenue this quarter.
Silence. Nobody really knows.
The advocacy happened...hopefully. The program didn't. Collectively, the organization slowly stopped feeding the very system it depended on to understand its advocacy program.
Reality Check
If AI helps facilitate twenty closed-won opportunities this quarter, but none are recorded, your executive dashboard still says zero.
One of the easiest mistakes to make in an AI-first world is assuming that successful interactions somehow become organizational knowledge on their own.
They don't.
If a customer agrees to speak with a prospect and nobody records it, the organization loses far more than a single activity.
The most valuable advocacy data isn't simply who your customers are.
It's everything they've done.
That's the story AI actually wants to read.
It's often said that AI needs good data.
That's true.
But operational history is far more valuable than static customer information.
Those aren't search results.Those are patterns.
Remove any one of those pieces and AI becomes little more than an exceptionally fast search engine.
Reality Check
Every workflow skipped today is a pattern AI won't discover tomorrow.
The AI revolution has created tremendous excitement, and rightly so. Finding the right advocate is becoming dramatically easier than it was only a few years ago.
That's worth celebrating.
Just don't confuse a better search experience with a better advocacy program. Search is only one chapter in the story.
The organizations that see the greatest return from AI won't necessarily be the ones with the most sophisticated models.
They'll be the ones with the richest operational history.
Those organizations won't use AI merely to answer the question, "Who should we ask?"
They'll use AI to answer far more valuable questions.
That's when AI stops behaving like a better Google search.
That's when it starts behaving like a strategic partner.
Finding the right advocate has always been the opening scene.
If your AI can find advocates but your program can't learn from using them, you've built a remarkable search engine instead of a remarkable advocacy program.
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